Proceedings of the Annual Conference of JSAI
Online ISSN : 2758-7347
35th (2021)
Session ID : 2D4-OS-7b-04
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Multi-task Delayed Feedback Model for Multiple Campaigns
*Kanata SATAKEMakoto YAMADAShota YASUIHisashi KASHIMA
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CONFERENCE PROCEEDINGS FREE ACCESS

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Abstract

CVR prediction is important in online advertising because it strongly reflects the interests of users. Many studies have performed CVR prediction on datasets with multiple advertisements, which may lead to problems inherent in multi-task learning, such as negative transfer. In this study, we introduce multi-task learning to Delayed Feedback Model, which is a typical method for CVR prediction. The proposed method can deal with problems such as task size imbalance and negative transfer, and can optimize appropriately for each advertisement. Experiments on multiple datasets confirm the effectiveness of the proposed method.

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© 2021 The Japanese Society for Artificial Intelligence
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